Image Classification | Mimi Bebe

Image classification is a core task in computer vision where algorithms assign a label or category to an entire image. This process involves training models on vast datasets of labeled images, enabling them to recognize patterns, features, and objects within new, unseen images. Key techniques include Convolutional Neural Networks (CNNs), which excel at learning hierarchical representations of visual data, from simple edges to complex object parts. The accuracy and robustness of classification depend heavily on the quality and diversity of the training data, as well as the chosen model architecture and hyperparameters. Applications range from content-based image retrieval and medical diagnostics to autonomous driving and content moderation.